Why must we discuss AI in marketing? What’s so wrong with marketing today that we need the incredible powers of artificial intelligence and machine learning to solve?

You’ve likely heard the cliché, “fast, cheap, good. Choose any two.” The premise is that we can have two out of three of these attributes, but we can’t have all three.

We can be fast and inexpensive, but at the cost of quality.

We can be inexpensive and high-quality, but at the expense of expediency.

We can be fast and high-quality, but such efficiency comes at a high price tag.

Yet, when we look at some of the largest, most successful companies, they manage to be successful at all three:

Tech giants such as Google and Facebook provide incredible services to billions of people at comparatively low costs.

Major consumer companies like Target and Walmart provide goods of high quality – especially compared to just two decades ago – at lower prices than ever, whenever we want it.

Is there anyone who isn’t familiar with Amazon ? (that’s reading this blog post)

What do all these companies have in common? Adoption of machine learning and artificial intelligence. What, as marketers, should we learn from them?

The Problems With Modern Marketing

Modern marketing at the average company usually manages to be fast, cheap, or good – but rarely two out of three, and almost never three out of three.

Many marketers, chasing speed, create low-quality garbage; take a read of some of the blogs online written in the marketing space or watch some of the marketing videos published on YouTube to see the consequence of chasing speed at the expense of everything else. They’re fast, but not much more.

Examine what other marketers attempt to do on little to no budget. They publish a blog post on social media posts in the hopes that someone notices, but with no budget, they create no results. At budget-stretched organizations, those same marketers are asked to wear twenty different hats, undermining their work quality for any one task. The result? They accomplish cheap, but not fast nor good.

Finally, many organizations are willing to invest in some level of marketing support, but because of a lack of adoption for the latest marketing technologies, marketers are unable to achieve speed or efficiency. They squander their organization’s investment, creating good marketing, but not fast or cheap.

At best, some companies are fortunate enough to achieve two out of three. They’re fast and cheap, or good and fast.

At worst, some companies manage to fail at all three.

Why Marketing Needs AI

The largest costs in marketing are human-related, from people to make content at scale to running advertising programs. These costs scale upwards at a disproportionate rate to impact delivered; adding more marketers scales at best linearly, because humans only have 24 hours in a day and do any one task relatively slowly.

Compare that with the capabilities of machine learning and artificial intelligence. If I have an analysis problem to solve and sufficient cloud computing infrastructure, instead of having one computer work on the problem, I simply “hire” thousands of temporary computers to instantly complete the job. Once done, those computers move onto other tasks. I could never hire thousands of people in a second and lay them off seconds later – but I can with machines.

If all the tasks in marketing were ideally suited for the ways humans work, this solution wouldn’t be much of a solution at all. However, the majority of tasks in marketing are highly repetitive, templated tasks. The email campaign we launch this week varies little from the one we launched a week ago. The social media posts we publish today aren’t substantially different than yesterday’s.

Thus, we have the ideal environment for AI: highly-repetitive tasks that we can outsource from humans to machines. In outsourcing these tasks, we increase the speed of our marketing by not having to wait for humans to finish their work at human speeds. We spend significantly less money because we spend less time. And, assuming we’ve trained our software correctly, the quality should be identical or better than what humans create in a rote tasks.

Fast. Cheap. Good.

We can have it all.

Will Marketing Still Need Humans?

For the foreseeable future, we will still need humans. Machines thus far have proven very poor at thinking across domains, at taking ideas from one domain and applying them to another. Machines are also poor at adapting to highly unpredictable situations, so when a black swan occurs – such as the Ice Bucket challenge, for example – we will still require human ingenuity to participate effectively.

Our machines alleviate the non-creative, rote work as soon as possible, freeing us up to do more of what we’re good at. As anyone with a to-do list knows, the list never gets shorter; as machines do more, our lists of what we will do will continue to grow as well.